11 research outputs found

    Paraneoplastic thrombocytosis in ovarian cancer

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    <p>Background: The mechanisms of paraneoplastic thrombocytosis in ovarian cancer and the role that platelets play in abetting cancer growth are unclear.</p> <p>Methods: We analyzed clinical data on 619 patients with epithelial ovarian cancer to test associations between platelet counts and disease outcome. Human samples and mouse models of epithelial ovarian cancer were used to explore the underlying mechanisms of paraneoplastic thrombocytosis. The effects of platelets on tumor growth and angiogenesis were ascertained.</p> <p>Results: Thrombocytosis was significantly associated with advanced disease and shortened survival. Plasma levels of thrombopoietin and interleukin-6 were significantly elevated in patients who had thrombocytosis as compared with those who did not. In mouse models, increased hepatic thrombopoietin synthesis in response to tumor-derived interleukin-6 was an underlying mechanism of paraneoplastic thrombocytosis. Tumorderived interleukin-6 and hepatic thrombopoietin were also linked to thrombocytosis in patients. Silencing thrombopoietin and interleukin-6 abrogated thrombocytosis in tumor-bearing mice. Anti–interleukin-6 antibody treatment significantly reduced platelet counts in tumor-bearing mice and in patients with epithelial ovarian cancer. In addition, neutralizing interleukin-6 significantly enhanced the therapeutic efficacy of paclitaxel in mouse models of epithelial ovarian cancer. The use of an antiplatelet antibody to halve platelet counts in tumor-bearing mice significantly reduced tumor growth and angiogenesis.</p> <p>Conclusions: These findings support the existence of a paracrine circuit wherein increased production of thrombopoietic cytokines in tumor and host tissue leads to paraneoplastic thrombocytosis, which fuels tumor growth. We speculate that countering paraneoplastic thrombocytosis either directly or indirectly by targeting these cytokines may have therapeutic potential. </p&gt

    Supplementary Figures 1-6 from Comparative Tumor Microenvironment Analysis of Primary and Recurrent Ovarian Granulosa Cell Tumors

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    S1. Heatmap of unsupervised hierarchical clustering of the top 1000 most variable genes.S2. Violin plots showing the expression levels of genes previously identified as differentially expressed genes between primary and recurrent tumors in Haltia et al., 2020.S3. Gene set enrichment analysis performed with GO terms and KEGG pathways showing that primarily immune-related and hormone-regulated gene sets expression are altered between primary and recurrent aGCTs.S4. Gene set enrichment analysis results showing that top enriched gene sets are significantly enriched in recurrent tumors in comparison with primary tumors.S5. Boxplot showing the fraction of each noncancerous cell type identified by CIBERSORTx (A) and xCell (B) in primary and recurrent tumor samples.S6. Heatmap showing the correlation between immune cells fractions.</p

    Cytogenetic analysis of major heterochromatic elements (especially Xh and Y) in Drosophila melanogaster, and the theory of “heterochromatin”

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